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Niels 2024-06-02 11:43:29 +02:00
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12
README.md
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@ -104,6 +104,18 @@ model.train(data='coco.yaml', epochs=500, batch=256, imgsz=640)
# model.push_to_hub("reponame") # model.push_to_hub("reponame")
``` ```
## Push to hub to 🤗
Optionally, you can push your fine-tuned model to the [Hugging Face hub](https://huggingface.co/) as a public or private model:
```python
# let's say you have fine-tuned a model for crop detection
model.push_to_hub("<your-hf-username-or-organization/yolov10-finetuned-crop-detection")
# you can also pass `private=True` if you don't want everyone to see your model
model.push_to_hub("<your-hf-username-or-organization/yolov10-finetuned-crop-detection", private=True)
```
## Prediction ## Prediction
Note that a smaller confidence threshold can be set to detect smaller objects or objects in the distance. Please refer to [here](https://github.com/THU-MIG/yolov10/issues/136) for details. Note that a smaller confidence threshold can be set to detect smaller objects or objects in the distance. Please refer to [here](https://github.com/THU-MIG/yolov10/issues/136) for details.
``` ```

4
ultralytics/engine/model.py
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@ -13,10 +13,8 @@ from ultralytics.hub.utils import HUB_WEB_ROOT
from ultralytics.nn.tasks import attempt_load_one_weight, guess_model_task, nn, yaml_model_load from ultralytics.nn.tasks import attempt_load_one_weight, guess_model_task, nn, yaml_model_load
from ultralytics.utils import ASSETS, DEFAULT_CFG_DICT, LOGGER, RANK, SETTINGS, callbacks, checks, emojis, yaml_load from ultralytics.utils import ASSETS, DEFAULT_CFG_DICT, LOGGER, RANK, SETTINGS, callbacks, checks, emojis, yaml_load
from huggingface_hub import PyTorchModelHubMixin
class Model(nn.Module):
class Model(nn.Module, PyTorchModelHubMixin):
""" """
A base class for implementing YOLO models, unifying APIs across different model types. A base class for implementing YOLO models, unifying APIs across different model types.

4
ultralytics/models/yolov10/model.py
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@ -4,7 +4,9 @@ from .val import YOLOv10DetectionValidator
from .predict import YOLOv10DetectionPredictor from .predict import YOLOv10DetectionPredictor
from .train import YOLOv10DetectionTrainer from .train import YOLOv10DetectionTrainer
class YOLOv10(Model): from huggingface_hub import PyTorchModelHubMixin
class YOLOv10(Model, PyTorchModelHubMixin, library_name="ultralytics", repo_url="https://github.com/THU-MIG/yolov10", tags=["object-detection", "yolov10"]):
def __init__(self, model="yolov10n.pt", task=None, verbose=False): def __init__(self, model="yolov10n.pt", task=None, verbose=False):
super().__init__(model=model, task=task, verbose=verbose) super().__init__(model=model, task=task, verbose=verbose)